Master the Coding Interview Big Tech (FAANG) Interviews.txt

Course Breakdown 
Interview Question #1 Two Sum 
How To Approach Our Problem 
Writing Our Brute Force Solution 
Testing Our Solution With Our Test Cases
Submitting To Leetcode 
Optimizing Our Solution 
Coding Our Optimal Solution 
Testing Our Optimal Solution With Our Test Cases 
Checking Performance On LeetCode 
Interview Question #2 - Container With Most Water 
Coming Up With Test Cases 
Thinking Through A Logical Brute Force Solution
Coding Out Our Brute Force Solution 
Stepping Through Our Code
Thinking About Our Optimal Solution 
Coding Our Optimal Solution And Testing On LeetCode 
Interview Question #3 - Trapping Rainwater 
Thinking About A Logical Solution 
Coding Our Brute Force Solution 
Figuring Out Our Optimization Strategy 
Coding Our Optimal Solution
Optimal Code And Testing On LeetCode 
Interview Question #4 -Typed Out Strings
Logic Of Our Brute Force Solution 
Coding Our Brute Force Solution
Space And Time Complexity
Coming Up With Optimal Solution 
Coding Our Optimal Solution
Submitting To LeetCode
Interview Question #5 - Longest Substring Without Repeating Characters 
Coming Up With A Brute Force Approach 
Coding Our Brute Force Solution 
Space And Time Complexity 
Sliding Window Technique 
Hints For Optimizing Our Solution 
Thinking About Optimal Solution 
Coding Our Optimal Solution
Optimal Code And Testing On LeetCode 
Intro To Palindromes 
Interview Question #6 - Valid Palindrome 
Almost A Palindrome 
Figuring Out Our Solution 
Coding Our Solution 
Linked List Introduction 
Basic Algorithm: Reverse a Linked List 
Thinking About Our Solution 
Coding Reverse A Linked List Solution 
Interview Question #7 - M, N Reversals 
Coming Up With A Logical Solution
Coding Our Solution 
Interview Question #8 - Merge Multi-Level Doubly Linked List 
Figuring Out Our Test Cases 
Thinking About Our Approach 
Coding Out Our Solution 
Interview Question #9 - Cycle Detection 
Floyd's Tortoise And Hare 
Coding Floyd's Algorithm 
Optional: Proof Of How Floyd's Algorithm Works
Intro to Stacks and Queues
Interview Question #10 - Valid Parentheses 
Walking Through Our Problem - Identifying The Need For A Stack 
Coding Our Solution With A Stack
Interview Question #11 - Minimum Brackets To Remove 
Thinking About Our Solution 
Coding Our Solution 
Question #12 - Implement Queue With Stacks 
Figuring Out Our Solution 
Coding Our Solution 
Introducing Recursion 
Optional: Tail Recursion 
Sorting 
Interview Question #13 - Kth Largest Element 
Insights From Quick Sort
Understanding Divide And Conquer 
Coding Quicksort Into Our Solution 
Understanding Hoare's Quickselect Algorithm
Coding Our Solution With Quickselect 
Understanding Binary Search 
How To Code Binary Search
Question #14 - Start And End Of Target In A Sorted Array 
Walking Through Our Solution 
Coding Our Solution 
Intro to Binary Trees 
Question #15 - Maximum Depth of Binary Tree 
Learning The Process For Solving Binary Tree Problems
Coding Our Solution 
Question #16 - Level Order Of Binary Tree
Walking Through Our Solution
Coding Out Level Order Traversal
Question #17 - Right Side View of Tree 
Understanding The Breadth First Search Approach 
Understanding The Depth First Search Approach 
Thinking About Pre-Order, In-Order, and Post-Order Traversals For Our Solution 
Completing Our DFS Solution 
Coding Our Final DFS Solution 
Question #18 - Number Of Nodes In Complete Tree
Thinking Deeply About A Full Binary Tree 
Figuring Out Number Of Nodes At Last Level 
Coding Out Our Full Solution 
Question #19 - Validate Binary Search Tree 
Thinking About Our Logical Solution 
Figuring Out Our Boundaries 
Coding Our Our Full Solution 
Introducing Heaps
Insertion In Heaps - Understanding Sift Up
Deletion In Heaps - Understanding Sift Down
Starting To Code Our Priority Queue Class 
Coding Our Insertion And Sift Up Methods 
Coding Our Deletion And Sift Down Methods 
Introducing 2D Arrays - What Are They? 
Depth First Search In 2D-Arrays 
Coding DFS - Setting Up For DFS 
Coding DFS - Implementing Recursive DFS 
Breadth First Search In 2D-Arrays
Coding BFS 
A General Approach To Thinking About Most Graph Questions
Question #20 Number Of Islands 
Approaching Our Problem - Thinking Deeply About The Values 
Approaching Our Problem - Thinking About Traversals
Coding Our Solution 
Thinking About Space And Time Complexity 
Question #21 Rotting Oranges
Figuring Out Our Initial Logic 
Figuring Out The Rest Of Our Solution 
Coding Out Our Solution 
Question #22 - Walls And Gates 
Figuring Out Our Logical Solution 
Coding Out Our Solution 
Introduction To The Types Of Graphs 
Representing Our Graphs - Adjacency List & Adjacency Matrix 
Breadth First Search In Graphs 
Coding BFS 
Depth First Search In Graphs 
Coding DFS 
Question #23 - Time Needed to Inform All Employees 
Verifying Our Constraints And Thinking About Test Cases 
How To Represent Our Graph As An Adjacency List 
Solving Our Problem Logically Using DFS Traversal 
Coding Our DFS Solution
Question #24 - Course Scheduler 
Thinking About Our Initial Solution - BFS 
Coding Out Our Initial BFS Solution 
What is Topological Sort? 
Thinking About A Solution With Topological Sort
Coding Our Final Solution 
Question #25 - Network Time Delay 
Thinking About How To Approach The Problem 
Greedy Method & What Is Dijkstra's Algorithm? 
Thinking About A Solution With Dijkstra's Algorithm 
Coding Our Solution With Dijkstra
Thinking About Time And Space Complexity Of Our Solution 
What is The Bellman-Ford Algorithm? - Conceptualizing Dynamic Programming 
What is The Bellman-Ford Algorithm? - The Algorithm Itself 
Coding Our Solution With Bellman-Ford 
Question #26 - Minimum Cost Of Climbing Stairs & How To Approach DP
Understanding & Identifying Recurrence Relation 
First Step - Recursive Solution From Recurrence Relation
Second Step - Memoizing Our Redundant Recursive Calls 
Coding Our Memoization Optimization 
Understanding The Bottom Up Approach (Tabulation) 
Third Step - Bottom Up Tabulation 
Fourth Step - Bottom Up Optimization 
Question #27 - Knight Probability In Chessboard 
Thinking About Test Cases To Help Us 
Identifying The Recurrence Relation
First Step - Recursive Solution From Recurrence Relation 
Second Step - Memoizing Our Redundant Recursive Calls 
Figuring Out The Logic For Our Bottom Up Solution 
Third Step - Bottom Up Tabulation 
Fourth Step - Bottom Up Optimization 
Understanding The Basics Of Backtracking 
Question #28 - Sudoku Solver 
Learning The Backtracking Template 
Applying Our Backtracking Template To Sudoku Solver Logic
Coding How To Get Box ID 
Setting Up Our Solution Code 
Coding The Recursive Backtracking Portion Of Our Solution 
Thinking About The Space And Time Complexity 
Understanding Interface Design & Question #29 - Monarchy
Figuring Out Our Test Cases 
Thinking About The Logical Of The Monarchy 
Coding Our Monarchy Solution 
Introducing Tries 
Question #30 - Implement Prefix Trie 
Understanding The Logic For Our Methods
Implementing Our Prefix Trie Data Structure Solution 
Section Overview 
What Is Good Code?
Big O and Scalability
O(n) 
O(1) 
Solution: Big O Calculation 
Solution: Big O Calculation 2
Simplifying Big O 
Big O Rule 1 
Big O Rule 2 
Big O Rule 3 
O(n^2)
Big O Rule 4 
Big O Cheat Sheet 
What Does This All Mean? 
O(n!) 
3 Pillars Of Programming
Space Complexity 
Exercise: Space Complexity 
Exercise: Twitter
Section Summary 
Arrays Introduction 
Static vs Dynamic Arrays 
Optional: Implementing An Array 
Hash Tables Introduction
Hash Function 
Hash Collisions 
Hash Tables VS Arrays 
Linked Lists Introduction
What Is A Linked List? 
Exercise: Why Linked Lists? 
Solution: Why Linked Lists? 
What Is A Pointer? 
Doubly Linked Lists 
Singly VS Doubly Linked Lists 
Linked Lists Review 
Stacks + Queues Introduction 
Stacks 
Queues 
Exercise: Stacks VS Queues 
Solution: Stacks VS Queues 
Stacks + Queues Review 
Trees Introduction
Binary Trees 
O(log n) 
Binary Search Tree 
Balanced VS Unbalanced BST 
BST Pros and Cons
Trie
Graph + Tree Traversals
BFS Introduction
DFS Introduction 
BFS vs DFS 
Exercise: BFS vs DFS
Solution: BFS vs DFS
Recursion Introduction 
Stack Overflow 
Anatomy Of Recursion 
Recursive VS Iterative 
When To Use Recursion 
Recursion Review 
Sorting Introduction
The Issue With sort() 
Sorting Algorithms
Bubble Sort 
Solution: Bubble Sort 
Selection Sort 
Solution: Selection Sort 
Dancing Algorithms 
Insertion Sort 
Solution: Insertion Sort 
Merge Sort and O(n log n) 
Solution: Merge Sort 
Quick Sort